2023-12-18
Promote empirical studies of the Portuguese economy using microdata
Grant free access to fully documented ready-to-use or customized data sets
Give access to great computational power and software
Provide technical, scientific, and computational support
Support the development of young researchers
Ensure the confidentiality and security of the microdata
Guarantee the reproducibility of the results
Micro data sets have different levels of confidentiality: low, medium, and high
If low:
If medium or high:
Data are always Anonymized: data sets are stripped of elements that allow for direct and indirect identification of companies or individuals.
Data sets contain unique unit identifiers common across data sets within each project (e.g.: tina and bina)
Data sets are based on a data extraction (“data freeze”) at a specific point in time
Labels are applied to all variables and value labels to all categorical variables (in PT and EN)
Detailed Manuals and metadata for all data sets
Data sets have registered DOIs and bib files for correct citation
Data sets are stored in efficient ways that minimize file size
Remote access from anywhere (using a safe connection with “No Machine”)
Inability to transfer, download, copy, paste or print data
Containers for operating system and statistical packages
Available software: R, Stata, Python, and Julia
Templates to help structure the code
Git for Version Control
After the Research Project is approved an Account is opened in the Server
Data for the project is prepared and placed in the server
Prepare the container according to researcher specifications
Meet with the researchers to guide them through the Server
mdata for handling metadata (available on BPLIM Github);Dummyfi for creating Dummy Data sets based on the metadata of the original data sets (soon to be available).List of Metadata Files Generated
Example of a Metadata File
List of Scripts to generate Dummy Data
WORKSHOP on Automation of the Research Process